Description of Invention
Treatment of stroke patients can be effectively carried out with the help of collateral circulation performance. Collateral circulation provides an alternative route to supply blood flow when the primary blood vessels are blocked in the brain. The scoring as it is now used is dependent on visual inspection, which can lead to discrepancy. In this study, a collateral circulation classification using deep learning was analyzed by using Cone Beam Computed Tomography (CBCT) images for the ischemic stroke patient. The remarkable performance of deep learning classification helps neuroradiologists with fast image classification. The experiments performed on CBCT images evidenced that the proposed method using ResNet50 architecture is indeed effective in classifying collateral circulation.